Message-ID: <8b3d3fe4-ab47-ea83-e2c2-ffc1d77f0488@gmail.com>
Date: 2019-05-07T16:31:14Z
From: Ben Bolker
Subject: A consultation about DF of the result of lmer
In-Reply-To: <70f1b859.675a.16a8ab261f0.Coremail.18754808835@163.com>
It's very hard to say without more information (try e.g. here
<https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example>
or look at other posts in the list archive
<https://stat.ethz.ch/pipermail/r-sig-mixed-models/>
A first guess is that you have a fixed-effect predictor that's
supposed to be a factor with 6 levels, but is actually being interpreted
as a numeric variable. If that's the case, then either changing it
within the data set
mydata$pred1 <- factor(mydata$pred1)
or doing it on the fly in your model
lmer(response ~ factor(pred1) + ...)
should fix the problem.
On 2019-05-05 9:11 p.m., ??? wrote:
> Dear,
> I am a graduated student who's topic is ecology. Recently, I am studying how to establish a liner mixed model to exclude the error caused by the difference of site by using lme4 in R. I found when I calculated p value by using the function of "Anova" of car package the Df is 1. But in fact the data set has 6 levels. Then I also operate according to the code of reference PDF of lme4 in P52(lmer) without any change. When run "anova(fm1, fm2)" I found the Df of fm1 also is 1. As I see if the Df is wrong the p value would be wrong either. I want to know how to correct my wrong. I will very appreciate your reply.
>
>
> Best regards,
> Rumeng He
> [[alternative HTML version deleted]]
>
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